论文
Graph pangenome captures missing heritability and empowers tomato breeding
https://www.nature.com/articles/s41586-022-04808-9#MOESM8
没有找到论文里的作图的代码,但是找到了部分做图数据,我们可以用论文中提供的原始数据模仿出论文中的图
今天的推文重复一下论文中的 Figure4d
Figure4e
散点图和箱线图
箱线图示例数据集
image.png作图代码
library(readxl)
dat01<-read_excel("data/20220711/41586_2022_4808_MOESM8_ESM.xlsx",
sheet = "Fig4e",
skip = 1)
dat01
library(ggplot2)
dat01$Type<-factor(dat01$Type,
levels = c("SNP","InDel","SV","SV array"))
ggplot(data=dat01,aes(x=Type,y=Accuracy))+
geom_line(aes(group=Metabolic),
color="grey")+
geom_boxplot(aes(color=Type),
fill="transparent")+
geom_point(aes(color=Type))+
theme_bw()+
theme(panel.grid = element_blank(),
legend.position = "none")+
scale_color_manual(values = c("#3288bd","#66c2a5",
"#f46d43","#f1226e"))+
labs(x=NULL,y="Prediction accuracy") -> p1
p1
image.png
散点图作图代码
dat02<-read_excel("data/20220711/41586_2022_4808_MOESM8_ESM.xlsx",
sheet = "Fig4d",
skip = 1)
dat02
library(paletteer)
library(latex2exp)
ggplot(data=dat02,aes(x=accuracy_snp,y=accuracy_sv))+
geom_point(aes(color=h2_snp))+
scale_x_continuous(limits = c(0,0.5),
expand = expansion(mult = c(0,0)))+
scale_y_continuous(limits = c(0,0.5),
expand = expansion(mult = c(0,0)))+
geom_abline(slope = 1,intercept = 0,lty="dashed")+
theme_bw()+
theme(panel.grid = element_blank(),
panel.border = element_blank(),
axis.line = element_line(),
legend.position = c(0.8,0.3))+
scale_color_paletteer_c(palette="grDevices::heat.colors",
direction = -1,
breaks=c(0.01,0.5,0.99),
labels=c(0,"0.50","1.00"),
name=TeX(r"(\textit{h}${^2}$)"))+
labs(x="Accuracy of SNP",y="Accuracy of SV") -> p2
p2
image.png
拼图
library(patchwork)
p2+p1
image.png
示例数据和代码可以自己到论文中获取,或者给本篇推文点赞,点击在看,然后留言获取
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